Staff AI Engineer: Enterprise LLM & Multi-Agent Systems

The Aspen Group

Northern (KY)

Hybrid

USD 170,000 - 200,000

Full time

5 days ago

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Benefits offered by this job

Paid time off

Health

Dental

Vision

401(k) savings plan with match

Job summary

The Aspen Group (TAG) is seeking a Staff AI Engineer to join our growing AI team. This hands-on role delivers innovative solutions for the healthcare enterprise, focusing on multi-agent systems, LLM-based architectures, and production-grade AI platforms.

The ideal candidate will have deep expertise in modern AI systems, agent orchestration, and cloud-native deployment, with strong Python skills and experience with Vertex AI and related frameworks. Join us to push AI at scale across TAG brands.

Qualifications

BS in Computer Science or related technology field or equivalent experience.
2+ years of experience in Agentic AI engineering.
4+ years of experience in AI/ML engineering and 8+ years of experience in software engineering.
Proven track record of building and deploying production-grade AI/ML systems at scale.
Deep understanding of modern AI model architectures (transformers, diffusion models) and system design.
Strong hands-on expertise with Vertex AI (training, pipelines, orchestration, deployment, monitoring) and Google's Agentic AI stack.
Hands-on with agent orchestration frameworks: Google ADK/Agentspace, LangChain, LangGraph, LlamaIndex, CrewAI or AutoGen.
Proficiency in Python, LLM integration workflows, MCP, and A2A orchestration.
Experience with distributed training, online inference, and low latency serving architectures.
Experience with Kubernetes, Cloud Run, and Dataflow/PubSub.

Responsibilities

Architect and develop enterprise-scale multi-agent systems leveraging LLMs and autonomous agent frameworks.
Design and implement RAG pipelines using BigQuery and Vertex AI Engine for knowledge grounding and accurate responses.
Optimize agents for orchestration, knowledge grounding, multi-step reasoning, and decision-making.
Design and implement distributed training workflows, online inference systems, and low latency serving architectures on Google cloud-native services.
Engineer scalable, secure, compliant AI fabric and agent workflows using Vertex AI and modern cloud-native tech.
Create reusable agent orchestration layers, observability hooks, and governance frameworks to accelerate adoption across TAG brands.
Partner with cross-functional stakeholders to translate business requirements into technical specs.
Own the full AI development lifecycle from data collection to deployment and monitoring.
Implement observability and automation strategies for AI system reliability and performance at scale.